Tunnel secondary lining intelligent spraying maintenance system based on micro-crack real-time scanning

Abstract

The invention discloses a tunnel secondary lining intelligent spraying maintenance system based on micro-crack real-time scanning, and relates to the technical field of tunnel maintenance. The system comprises a scanning unit, a track platform, a processing unit, a spraying module and a mechanical arm, the scanning unit comprises a laser module and a visual module, the output ends of the laser module and the visual module are both connected with the input end of the processing unit, and a port of the track platform communicates with a port of the processing unit; the output end of the processing unit is connected with the input end of the spraying module and the input end of the mechanical arm, the track platform is a suspension type track car, and the suspension type track car is installed on a track laid on the inner top face of a tunnel. Different key spraying maintenance modes can be conveniently executed, and the micro-fracture prediction program can be continuously corrected by presetting and continuously updating the adjusting parameters.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel maintenance, and in particular to an intelligent spraying maintenance system for a tunnel secondary lining based on real-time scanning of micro-cracks. Background Art

[0002] After the construction of the concrete wall in the tunnel, affected by the temperature and humidity, it is necessary to spray it at irregular intervals to avoid problems such as cracking of the wall. Generally, a manual push device or a water pipe is used for spraying, or an automated spraying device is used to spray and maintain the tunnel secondary lining.

[0003] The current spraying device can only spray the surface inside the tunnel evenly. When the stress and dryness level in different parts of the tunnel are different, the microcracks in the tunnel are unevenly distributed and the degree of cracking is different. Focused spraying maintenance is required for microcracks of different degrees to prevent the deterioration of the crack distribution in the tunnel. Therefore, how to evaluate the microcracks and focus on spraying maintenance is a technical problem that technical personnel in this field need to solve. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent spraying maintenance system for the secondary lining of a tunnel based on real-time scanning of micro-cracks, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a tunnel secondary lining intelligent spraying maintenance system based on real-time scanning of microcracks, comprising a scanning unit, a track platform, a processing unit, a spraying module and a mechanical arm, wherein the scanning unit comprises a laser module and a visual module, the output ends of the laser module and the visual module are both connected to the input end of the processing unit, the port of the track platform establishes communication with the port of the processing unit, and the output end of the processing unit is respectively connected to the input end of the spraying module and the input end of the mechanical arm;

[0006] The track platform is a suspended track vehicle, which is installed on the track laid on the top surface of the tunnel. The suspended track vehicle is driven by an internal motor to move on the track. The visual module includes three image sensors, and the directions of the three image sensors along the track direction are horizontally left, horizontally right and vertically downward. The three image sensors are used to obtain image information of the area where the track platform is located and transmit it to the processing unit. The laser module includes three infrared laser scanners, and the directions of the three infrared laser scanners along the track direction are horizontally left, horizontally right and vertically downward. The three infrared laser scanners are used to obtain depth information of the area where the track platform is located and transmit it to the processing unit. The spray module includes a water tank, a water pump and an atomizing nozzle. The water tank, the water pump and the atomizing nozzle are connected through a water pipe. The water pump draws water from the water tank and sprays it externally through the atomizing nozzle. The mechanical arm is a six-axis mechanical arm, and the atomizing nozzle is fixed to the end of the mechanical arm. The scanning unit, the spray module, the processing unit and the mechanical arm are all installed at the bottom of the track platform. When the track platform moves on the track in the tunnel, it will drive the mechanical arm, the scanning unit and the spray module to move synchronously;

[0007] The processing unit executes a first scanning program to obtain a spatial model of the tunnel, executes a microcrack analysis program to obtain the coordinates of all microcracks in the spatial model, outputs the coordinates of all microcracks as a report for staff to view, and the staff goes to the tunnel to manually evaluate all microcracks according to the coordinates of the microcracks. The evaluation results of the manual evaluation are divided into three types: slight, ordinary, and severe. The staff makes subjective evaluation and judgment based on the distribution density, length, and depth of the microcracks. The scope of manual evaluation includes microcracks that are not found by the microcrack analysis program. The staff uses a sign graphic to replace the evaluation result and pastes the sign graphic on the top of all microcracks. The processing unit executes a second scanning program to obtain the evaluation results of all microcracks. The processing unit executes a microcrack prediction program to obtain a spray point Pst and a spray amount Q. The processing unit controls the track platform, the robotic arm, and the spray module according to the spray point Pst and the spray amount Q to spray and maintain all microcracks in the tunnel.

[0008] After the spray module completes spray maintenance on all microcracks, the processing unit executes the microcrack analysis program again at a fixed interval of 12 hours to obtain the newly added microcrack coordinates. The processing unit updates the preset adjustment parameters fix according to the newly added microcrack coordinates. The processing unit then executes the microcrack prediction program and subsequent spray maintenance according to the updated adjustment parameters fix.

[0009] Furthermore, when the first scanning program is executed, the processing unit sends scanning instructions to the laser module and the visual module respectively, and the processing unit sends a displacement instruction to the track platform. After receiving the displacement instruction, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel;

[0010] When the track platform starts to move, the three image sensors of the vision module acquire the image information in the tunnel in real time and transmit it to the processing unit, and the three infrared laser scanners acquire the depth information in the tunnel in real time and transmit it to the processing unit;

[0011] A displacement encoder is provided inside the track platform, which records the displacement distance of the track platform in real time. The track platform transmits its own displacement distance to the processing unit, which establishes a spatial coordinate system. The processing unit marks the starting point of the track platform movement as the origin of the spatial coordinate system, marks the track in the tunnel as the x-axis of the spatial coordinate system, marks the width of the tunnel as the y-axis of the spatial coordinate system, and marks the height of the tunnel as the z-axis of the spatial coordinate system. The unit length of the spatial coordinate system is meter. The length of the track in the tunnel is obtained through the displacement distance of the track platform, and the width and height of the tunnel are obtained from the depth information.

[0012] The processing unit stitches the image information of the three image sensors to obtain a complete image model of the tunnel, stitches the depth information of the three infrared laser scanners to obtain a complete depth model of the tunnel, and aligns and overlaps the image modules and the depth model and inputs them into the spatial coordinate system to obtain a spatial model of the tunnel;

[0013] When the track platform moves on the track in the tunnel, the processing unit controls the end of the robotic arm to make left and right reciprocating arc movements. At the same time, the processing unit controls the spray module to spray the secondary lining surface in the tunnel as the end of the robotic arm moves. When the processing unit obtains a complete spatial model of the tunnel, the spray module completes a comprehensive spraying of the secondary lining surface in the tunnel, thereby achieving preliminary maintenance of the tunnel secondary lining and facilitating subsequent focused spraying maintenance of microcracks.

[0014] Furthermore, when the microcrack analysis program is executed, the processing unit calculates all pixels in the image information and converts them into grayscale pixels. The processing unit calculates the grayscale value Grey of each pixel according to the formula Grey = Red × 0.299 + Green × 0.587 + Blue × 0.114. The grayscale value Grey has a value range of 0-255, Red is the pixel red channel value, Green is the pixel green channel value, and Blue is the pixel blue channel value;

[0015] The processing unit counts the mode of the grayscale values ​​Grey of all grayscale image pixels, and marks the grayscale image pixels with the grayscale value Grey within the range of ±10% of the mode as the background. The mode of the grayscale value Grey of the grayscale image pixels represents the grayscale value Grey appears the most times. The mode is the background color of the image information. It is necessary to filter out the background color before the processing unit identifies the microcracks in the image information, which can improve the recognition speed of the microcracks. The image information is affected by the brightness in the tunnel, and the recognition of the background is likely to produce errors. Therefore, the grayscale value Grey marking range of the background is expanded to improve the fault tolerance rate of background recognition;

[0016] The processing unit removes all grayscale pixels marked as background in the image information, and subtracts grayscale pixels with grayscale values ​​Grey less than 50 from adjacent pixels to obtain adjacent pixel differences. When the adjacent pixel difference between the grayscale pixels with grayscale values ​​Grey less than 50 and adjacent pixels is less than or equal to 10, the processing unit connects the grayscale pixels with grayscale values ​​Grey less than 50 and the adjacent pixels. When the adjacent pixel difference between the grayscale pixels with grayscale values ​​Grey less than 50 and the adjacent pixels is greater than 10, the processing unit disconnects the two pixels. When the processing unit completes the calculation of the adjacent pixel differences between all grayscale pixels with grayscale values ​​Grey less than 50 and adjacent pixels, the processing unit marks the continuously connected grayscale pixels as visual cracks.

[0017] The processing unit aligns and overlaps all the depth information with the image information, and establishes a depth curve graph. The vertical axis of the depth curve graph is the depth information, and the horizontal axis is the displacement distance of the track platform. The processing unit inputs the depth information corresponding to the visual crack in the image information into the depth curve graph to obtain the depth curve at the visual crack. The processing unit takes two adjacent points A (p1, q1) and B (p2, q2) in the depth curve, where p1 and p2 are the displacement distances of the track platform, and q1 and q2 are the depth information. The processing unit calculates the depth curve according to the formula Calculate the slope k between point A and point B. When the slope k is ≥ 0.75, the processing unit determines that the trend of the depth curve is a steep rise or a steep drop, indicating that the depth information at the visual crack fluctuates greatly and there is a real crack. The processing unit marks the visual crack with a steep rise or a steep drop in the depth curve as a microcrack.

[0018] The processing unit obtains the displacement distance of the track platform at the microcrack and marks it as length X. The processing unit marks the depth information obtained by the infrared laser scanner facing horizontally to the left or horizontally to the right at the microcrack as width Y. When the microcrack is located on the left side of the forward direction of the track platform, the processing unit uses the infrared laser scanner facing horizontally to the left. When the microcrack is located on the right side of the forward direction of the track platform, the processing unit uses the infrared laser scanner facing horizontally to the right. The processing unit marks the depth information obtained by the infrared laser scanner facing vertically downward at the microcrack as height Z. The processing unit binds the length X, width Y and height Z and records them as the coordinates of the microcrack.

[0019] Furthermore, the sign graphics corresponding to the evaluation results of the manual evaluation are circle, triangle and square respectively, and the filling color of the sign graphics is red to increase the contrast with the tunnel background color, which is convenient for the processing unit to identify;

[0020] When the second scanning program is executed, the processing unit sends a displacement command to the track platform. After receiving the displacement command, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel. When the track platform starts to move, the processing unit obtains image information from the three image sensors of the visual module. The processing unit extracts red pixels in the image information. The red channel value Red of the red pixel is 255, the green channel value Green is 0, and the blue channel value Blue is 0. The processing unit marks the clustered red pixels as identification targets.

[0021] The processing unit scans the edge of the identified target. When the edge of the identified target is a continuous arc without corners, the processing unit will mark the identified target as a circular sign graphic, and the corresponding microcrack assessment result is mild. When the edge of the identified target is a straight line and has three corners, the processing unit will mark the identified target as a triangular sign graphic, and the corresponding microcrack assessment result is ordinary. When the edge of the identified target is a straight line and has four corners, the processing unit will mark the identified target as a square sign graphic, and the corresponding microcrack assessment result is severe.

[0022] Furthermore, when the microcrack prediction program is executed, the processing unit obtains all microcrack tip connection line marks in the image information as reference lines, calculates the angle θ1 between the reference line and the horizontal direction, and calculates the angle θ2 between the reference line and the vertical direction, θ1 and θ2 satisfy the condition θ1+θ2=90°, and presets the reference angle θ3. The processing unit compares the angle θ1 and the angle θ2 of the microcrack reference line, if θ1<θ2, then θ3=θ1, if θ2<θ1, then θ3=θ2, and if θ1=θ2, then θ3=θ1=θ2;

[0023] The processing unit counts the number of pixels arranged in the vertical direction of each microcrack and its own reference line in the image information, Wpix, where the number of pixels arranged pix represents the quantized width value of the microcrack. The processing unit calculates the reference line pixel length Lpix of each microcrack in the image information. The processing unit calculates the maximum depth D of each microcrack in the depth information.

[0024] The processing unit presets weight coefficients w1, w2 and w3, and the weight coefficients w1, w2 and w3 satisfy the condition w1+w2+w3=1. The specific values ​​of the weight coefficients w1, w2 and w3 are determined according to the number of microcracks in the tunnel, and the adjustment parameter fix is ​​preset. The initial values ​​of the adjustment parameter fix are 0.8, 0.5 and 0.3, respectively, corresponding to slight, ordinary and severe microcracks;

[0025] The evaluation result is slight micro cracks, and the analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is a common microcrack. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is serious microcracks. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcrack, where Pst(θ) is the angle between the spray point Pst and the midpoint of the reference line, and Pst(L) is the distance between the spray point Pst and the midpoint of the reference line. The microcrack prediction program stops.

[0026] The update process of the adjustment parameter fix is ​​as follows:

[0027] The processing unit calculates the distance Dn between the newly added microcrack coordinates and the spray point Pst. If the value of the distance Dn is equal to or greater than the length of the original microcrack reference line, it means that the prediction is deviated and the effect of the spraying maintenance is not obvious. The processing unit will adjust the initial value of the adjustment parameter fix down by a value of 0.01. Conversely, if the value of the distance Dn is less than the length of the original microcrack reference line, it means that the prediction is more accurate and the effect of the spraying maintenance is obvious. The processing unit will adjust the initial value of the adjustment parameter fix up by a value of 0.01.

[0028] The present invention has the following beneficial effects:

[0029] 1. The automatic scanning of the scanning unit can quickly locate the coordinates of microcracks, avoiding manual investigation. The microcracks can be classified through manual evaluation, which facilitates the implementation of different key spraying maintenance methods and prevents the deterioration of crack distribution in the tunnel.

[0030] 2. By presetting and updating the adjustment parameters, the microcrack prediction program can be continuously corrected, and the effect of key spraying maintenance can be continuously optimized.

[0031] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0033] Figure 1 This is a block diagram of the tunnel secondary lining intelligent spraying maintenance system based on real-time scanning of micro-cracks of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] See also Figure 1 The present invention provides a technical solution: an intelligent spraying maintenance system for a tunnel secondary lining based on real-time scanning of microcracks, comprising a scanning unit, a track platform, a processing unit, a spraying module and a mechanical arm, wherein the scanning unit comprises a laser module and a visual module, the output ends of the laser module and the visual module are both connected to the input end of the processing unit, the port of the track platform establishes communication with the port of the processing unit, and the output end of the processing unit is respectively connected to the input end of the spraying module and the input end of the mechanical arm;

[0036] The track platform is a suspended track vehicle, which is installed on the track laid on the top surface of the tunnel. The suspended track vehicle is driven by an internal motor to move on the track. The visual module includes three image sensors, and the directions of the three image sensors along the track direction are horizontally left, horizontally right and vertically downward. The three image sensors are used to obtain image information of the area where the track platform is located and transmit it to the processing unit. The laser module includes three infrared laser scanners, and the directions of the three infrared laser scanners along the track direction are horizontally left, horizontally right and vertically downward. The three infrared laser scanners are used to obtain depth information of the area where the track platform is located and transmit it to the processing unit. The spray module includes a water tank, a water pump and an atomizing nozzle. The water tank, the water pump and the atomizing nozzle are connected by a water pipe. The water pump draws water from the water tank and sprays it externally through the atomizing nozzle. The robotic arm is a six-axis robotic arm, and the atomizing nozzle is fixed to the end of the robotic arm. The scanning unit, the spray module, the processing unit and the robotic arm are all installed at the bottom of the track platform. When the track platform moves on the track in the tunnel, it will drive the robotic arm, the scanning unit and the spray module to move synchronously;

[0037] The processing unit executes a first scanning program to obtain a spatial model of the tunnel, executes a microcrack analysis program to obtain the coordinates of all microcracks in the spatial model, outputs the coordinates of all microcracks as a report for staff to view, and the staff goes to the tunnel to manually evaluate all microcracks according to the coordinates of the microcracks. The evaluation results of the manual evaluation are divided into three types: slight, ordinary, and severe. The staff makes subjective evaluation and judgment based on the distribution density, length, and depth of the microcracks. The scope of manual evaluation includes microcracks that are not found by the microcrack analysis program. The staff uses a sign graphic to replace the evaluation result and pastes the sign graphic on the top of all microcracks. The processing unit executes a second scanning program to obtain the evaluation results of all microcracks. The processing unit executes a microcrack prediction program to obtain a spray point Pst and a spray amount Q. The processing unit controls the track platform, the robotic arm, and the spray module according to the spray point Pst and the spray amount Q to spray and maintain all microcracks in the tunnel.

[0038] After the spray module completes spray maintenance on all microcracks, the processing unit executes the microcrack analysis program again at a fixed interval of 12 hours to obtain the newly added microcrack coordinates. The processing unit updates the preset adjustment parameters fix according to the newly added microcrack coordinates. The processing unit then executes the microcrack prediction program and subsequent spray maintenance according to the updated adjustment parameters fix.

[0039] When the first scanning program is executed, the processing unit sends scanning instructions to the laser module and the visual module respectively, and the processing unit sends a displacement instruction to the track platform. After receiving the displacement instruction, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel;

[0040] When the track platform starts to move, the three image sensors of the vision module acquire the image information in the tunnel in real time and transmit it to the processing unit, and the three infrared laser scanners acquire the depth information in the tunnel in real time and transmit it to the processing unit;

[0041] A displacement encoder is provided inside the track platform, which records the displacement distance of the track platform in real time. The track platform transmits its own displacement distance to the processing unit, which establishes a spatial coordinate system. The processing unit marks the starting point of the track platform movement as the origin of the spatial coordinate system, marks the track in the tunnel as the x-axis of the spatial coordinate system, marks the width of the tunnel as the y-axis of the spatial coordinate system, and marks the height of the tunnel as the z-axis of the spatial coordinate system. The unit length of the spatial coordinate system is meter. The length of the track in the tunnel is obtained through the displacement distance of the track platform, and the width and height of the tunnel are obtained from the depth information.

[0042] The processing unit stitches the image information of the three image sensors to obtain a complete image model of the tunnel, stitches the depth information of the three infrared laser scanners to obtain a complete depth model of the tunnel, and aligns and overlaps the image modules and the depth model and inputs them into the spatial coordinate system to obtain a spatial model of the tunnel;

[0043] When the track platform moves on the track in the tunnel, the processing unit controls the end of the robotic arm to make left and right reciprocating arc movements. At the same time, the processing unit controls the spray module to spray the secondary lining surface in the tunnel as the end of the robotic arm moves. When the processing unit obtains a complete spatial model of the tunnel, the spray module completes a comprehensive spraying of the secondary lining surface in the tunnel, thereby achieving preliminary maintenance of the tunnel secondary lining and facilitating subsequent focused spraying maintenance of microcracks.

[0044] When the microcrack analysis program is executed, the processing unit converts all pixels in the image information into grayscale pixels. The processing unit calculates the grayscale value Grey of each pixel according to the formula Grey = Red × 0.299 + Green × 0.587 + Blue × 0.114. The grayscale value Grey has a value range of 0-255, Red is the pixel red channel value, Green is the pixel green channel value, and Blue is the pixel blue channel value;

[0045] The processing unit counts the mode of the grayscale values ​​Grey of all grayscale image pixels, and marks the grayscale image pixels with the grayscale value Grey within the range of ±10% of the mode as the background. The mode of the grayscale value Grey of the grayscale image pixels represents the grayscale value Grey appears the most times. The mode is the background color of the image information. It is necessary to filter out the background color before the processing unit identifies the microcracks in the image information, which can improve the recognition speed of the microcracks. The image information is affected by the brightness in the tunnel, and the recognition of the background is likely to produce errors. Therefore, the grayscale value Grey marking range of the background is expanded to improve the fault tolerance rate of background recognition;

[0046] The processing unit removes all grayscale pixels marked as background in the image information, and subtracts grayscale pixels with grayscale values ​​Grey less than 50 from adjacent pixels to obtain adjacent pixel differences. When the adjacent pixel difference between the grayscale pixels with grayscale values ​​Grey less than 50 and adjacent pixels is less than or equal to 10, the processing unit connects the grayscale pixels with grayscale values ​​Grey less than 50 and the adjacent pixels. When the adjacent pixel difference between the grayscale pixels with grayscale values ​​Grey less than 50 and the adjacent pixels is greater than 10, the processing unit disconnects the two pixels. When the processing unit completes the calculation of the adjacent pixel differences between all grayscale pixels with grayscale values ​​Grey less than 50 and adjacent pixels, the processing unit marks the continuously connected grayscale pixels as visual cracks.

[0047] The processing unit aligns and overlaps all the depth information with the image information, and establishes a depth curve graph. The vertical axis of the depth curve graph is the depth information, and the horizontal axis is the displacement distance of the track platform. The processing unit inputs the depth information corresponding to the visual crack in the image information into the depth curve graph to obtain the depth curve at the visual crack. The processing unit takes two adjacent points A (p1, q1) and B (p2, q2) in the depth curve, where p1 and p2 are the displacement distances of the track platform, and q1 and q2 are the depth information. The processing unit calculates the depth curve according to the formula Calculate the slope k between point A and point B. When the slope k is ≥ 0.75, the processing unit determines that the trend of the depth curve is a steep rise or a steep drop, indicating that the depth information at the visual crack fluctuates greatly and there is a real crack. The processing unit marks the visual crack with a steep rise or a steep drop in the depth curve as a microcrack.

[0048] The processing unit obtains the displacement distance of the track platform at the microcrack and marks it as length X. The processing unit marks the depth information obtained by the infrared laser scanner facing horizontally to the left or horizontally to the right at the microcrack as width Y. When the microcrack is located on the left side of the forward direction of the track platform, the processing unit uses the infrared laser scanner facing horizontally to the left. When the microcrack is located on the right side of the forward direction of the track platform, the processing unit uses the infrared laser scanner facing horizontally to the right. The processing unit marks the depth information obtained by the infrared laser scanner facing vertically downward at the microcrack as height Z. The processing unit binds the length X, width Y and height Z and records them as the coordinates of the microcrack.

[0049] The sign graphics corresponding to the manual evaluation results are circle, triangle and square respectively, and the sign graphics are filled with red to increase the contrast with the tunnel background color, which is convenient for the processing unit to identify;

[0050] When the second scanning program is executed, the processing unit sends a displacement command to the track platform. After receiving the displacement command, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel. When the track platform starts to move, the processing unit obtains image information from the three image sensors of the visual module. The processing unit extracts red pixels in the image information. The red channel value Red of the red pixel is 255, the green channel value Green is 0, and the blue channel value Blue is 0. The processing unit marks the clustered red pixels as identification targets.

[0051] The processing unit scans the edge of the identified target. When the edge of the identified target is a continuous arc without corners, the processing unit will mark the identified target as a circular sign graphic, and the corresponding microcrack assessment result is mild. When the edge of the identified target is a straight line and has three corners, the processing unit will mark the identified target as a triangular sign graphic, and the corresponding microcrack assessment result is ordinary. When the edge of the identified target is a straight line and has four corners, the processing unit will mark the identified target as a square sign graphic, and the corresponding microcrack assessment result is severe.

[0052] When the microcrack prediction program is executed, the processing unit obtains all microcrack tip connection line marks in the image information as reference lines, calculates the angle θ1 between the reference line and the horizontal direction, and calculates the angle θ2 between the reference line and the vertical direction. θ1 and θ2 satisfy the condition θ1+θ2=90°. The processing unit presets a reference angle θ3. The processing unit compares the angle θ1 and the angle θ2 of the microcrack reference line. If θ1<θ2, then θ3=θ1. If θ2<θ1, then θ3=θ2. If θ1=θ2, then θ3=θ1=θ2.

[0053] The processing unit counts the number of pixels arranged in the vertical direction of each microcrack and its own reference line in the image information, Wpix, where the number of pixels arranged pix represents the quantized width value of the microcrack. The processing unit calculates the reference line pixel length Lpix of each microcrack in the image information. The processing unit calculates the maximum depth D of each microcrack in the depth information.

[0054] The processing unit presets weight coefficients w1, w2 and w3, and the weight coefficients w1, w2 and w3 satisfy the condition w1+w2+w3=1. The specific values ​​of the weight coefficients w1, w2 and w3 are determined according to the number of microcracks in the tunnel, and the adjustment parameter fix is ​​preset. The initial values ​​of the adjustment parameter fix are 0.8, 0.5 and 0.3, respectively, corresponding to slight, ordinary and severe microcracks;

[0055] The evaluation result is slight micro cracks, and the analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is a common microcrack. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is serious microcracks. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcrack, where Pst(θ) is the angle between the spray point Pst and the midpoint of the reference line, and Pst(L) is the distance between the spray point Pst and the midpoint of the reference line. The microcrack prediction program stops.

[0056] The update process of the adjustment parameter fix is ​​as follows:

[0057] The processing unit calculates the distance Dn between the newly added microcrack coordinates and the spray point Pst. If the value of the distance Dn is equal to or greater than the length of the original microcrack reference line, it means that the prediction is deviated and the effect of the spraying maintenance is not obvious. The processing unit will adjust the initial value of the adjustment parameter fix down by a value of 0.01. Conversely, if the value of the distance Dn is less than the length of the original microcrack reference line, it means that the prediction is more accurate and the effect of the spraying maintenance is obvious. The processing unit will adjust the initial value of the adjustment parameter fix up by a value of 0.01.

[0058] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent spraying maintenance system for secondary lining of a tunnel based on real-time scanning of microcracks, comprising a scanning unit, a track platform, a processing unit, a spraying module and a mechanical arm, wherein the scanning unit comprises a laser module and a visual module, the output ends of the laser module and the visual module are both connected to the input end of the processing unit, the port of the track platform establishes communication with the port of the processing unit, and the output end of the processing unit is respectively connected to the input end of the spraying module and the input end of the mechanical arm; characterized in that: The track platform is a suspended track vehicle, which is installed on the track laid on the top surface of the tunnel and is driven by an internal motor to move on the track. The visual module includes three image sensors, which are used to obtain image information of the area where the track platform is located and transmit it to the processing unit. The laser module includes three infrared laser scanners, which are used to obtain depth information of the area where the track platform is located and transmit it to the processing unit. The spray module includes a water tank, a water pump and an atomizing nozzle, which is fixed to the end of the mechanical arm. The scanning unit, the spray module, the processing unit and the mechanical arm are all installed at the bottom of the track platform. When the track platform moves on the track in the tunnel, it drives the mechanical arm, the scanning unit and the spray module to move synchronously. The processing unit executes a first scanning program to obtain a spatial model of the tunnel, executes a microcrack analysis program to obtain the coordinates of all microcracks in the spatial model, and manually evaluates all microcracks. The manual evaluation range includes microcracks that are not found by the microcrack analysis program. The staff uses a sign graphic to replace the evaluation result, and pastes the sign graphic on the top of all microcracks. The second scanning program is executed to obtain the evaluation results of all microcracks, and the microcrack prediction program is executed to obtain the spray point Pst and the spray amount Q. According to the spray point Pst and the spray amount Q, the track platform, the mechanical arm and the spray module are respectively controlled to spray and maintain all microcracks in the tunnel; After the spray module completes spray maintenance on all microcracks, at a fixed interval, the processing unit executes the microcrack analysis program again to obtain the newly added microcrack coordinates, updates the preset adjustment parameters fix according to the newly added microcrack coordinates, and then executes the microcrack prediction program and subsequent spray maintenance according to the updated adjustment parameters fix.

2. The tunnel secondary lining intelligent spraying maintenance system based on real-time microcrack scanning according to claim 1 is characterized in that: When the first scanning program is executed, the processing unit sends scanning instructions to the laser module and the visual module respectively, and the processing unit sends a displacement instruction to the track platform. After receiving the displacement instruction, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel; When the track platform starts to move, the three image sensors of the vision module acquire the image information in the tunnel in real time and transmit it to the processing unit, and the three infrared laser scanners acquire the depth information in the tunnel in real time and transmit it to the processing unit; A displacement encoder is provided inside the track platform, which records the displacement distance of the track platform in real time. The track platform transmits its own displacement distance to the processing unit to establish a spatial coordinate system, mark the starting point of the track platform movement as the origin of the spatial coordinate system, mark the track in the tunnel as the x-axis of the spatial coordinate system, mark the width of the tunnel as the y-axis of the spatial coordinate system, and mark the height of the tunnel as the z-axis of the spatial coordinate system. The unit length of the spatial coordinate system is meter. The processing unit stitches the image information of the three image sensors to obtain a complete image model of the tunnel, stitches the depth information of the three infrared laser scanners to obtain a complete depth model of the tunnel, aligns and overlaps the image modules and the depth model and inputs them into the spatial coordinate system to obtain a spatial model of the tunnel; When the track platform moves on the track in the tunnel, the processing unit controls the end of the robotic arm to make left and right reciprocating arc movements, and at the same time controls the spray module to spray the secondary lining surface in the tunnel as the end of the robotic arm moves. When the processing unit obtains a complete spatial model of the tunnel, the spray module completes a comprehensive spraying of the secondary lining surface in the tunnel.

3. The tunnel secondary lining intelligent spraying maintenance system based on real-time microcrack scanning according to claim 1 is characterized in that: When the microcrack analysis program is executed, the processing unit converts all pixels in the image information into grayscale pixels, and calculates the grayscale value Grey of each pixel according to the formula Grey = Red × 0.299 + Green × 0.587 + Blue × 0.

114. The grayscale value Grey has a value range of 0-255, Red is the pixel red channel value, Green is the pixel green channel value, and Blue is the pixel blue channel value; Count the mode of all grayscale image pixels in the grayscale value Grey, and mark all grayscale image pixels with grayscale values ​​Grey within the range of ±10% of the mode as background; All grayscale pixels marked as background in the image information are removed. The processing unit subtracts grayscale pixels with grayscale values ​​less than 50 from adjacent pixels to obtain adjacent pixel differences. When the adjacent pixel difference is less than or equal to 10, the two pixels are connected. When the adjacent pixel difference is greater than 10, the two pixels are disconnected. After all adjacent pixel differences are calculated, the continuously connected grayscale pixels are marked as visual cracks. The processing unit aligns and overlaps all the depth information with the image information to establish a depth curve graph. The vertical axis of the depth curve graph is the depth information, and the horizontal axis is the displacement distance of the track platform. The depth information corresponding to the visual crack in the image information is input into the depth curve graph to obtain the depth curve at the visual crack. Take two adjacent points A (p1, q1) and B (p2, q2) in the depth curve, where p1 and p2 are the displacement distances of the track platform, and q1 and q2 are the depth information. According to the formula Calculate the slope k between point A and point B. When the slope k is ≥ 0.75, determine whether the depth curve has a steep rise or fall trend, and mark the visual cracks with a steep rise or fall trend as microcracks. The processing unit obtains the displacement distance of the track platform at the microcrack and marks it as length X, marks the depth information obtained by the infrared laser scanner facing horizontally to the left or horizontally to the right at the microcrack as width Y, and marks the depth information obtained by the infrared laser scanner facing vertically downward at the microcrack as height Z, and binds the length X, width Y and height Z and records them as the coordinates of the microcrack.

4. The tunnel secondary lining intelligent spraying maintenance system based on real-time micro-crack scanning according to claim 1 is characterized in that: The symbol graphics corresponding to the manual evaluation results are circle, triangle and square respectively, and the filling color of the symbol graphics is red; When the second scanning program is executed, the processing unit sends a displacement command to the track platform. After receiving the displacement command, the track platform starts the motor to drive itself to move at a constant speed along the track in the tunnel. When the track platform starts to move, it obtains image information from the three image sensors of the vision module, extracts red pixels in the image information, and marks the clustered red pixels as the recognition target; The processing unit scans the edge of the identified target. When the edge of the identified target is a continuous arc with no corners, the identified target is marked with a circular sign graphic, and the corresponding microcrack assessment result is mild. When the edge of the identified target is a straight line and has three corners, the identified target is marked with a triangular sign graphic, and the corresponding microcrack assessment result is ordinary. When the edge of the identified target is a straight line and has four corners, the identified target is marked with a square sign graphic, and the corresponding microcrack assessment result is severe.

5. The tunnel secondary lining intelligent spraying maintenance system based on real-time microcrack scanning according to claim 1 is characterized in that: When the microcrack prediction program is executed, the processing unit obtains all microcrack tip connection lines in the image information as reference lines, calculates the angle θ1 between the reference line and the horizontal direction, and calculates the angle θ2 between the reference line and the vertical direction. θ1 and θ2 satisfy the condition θ1+θ2=90°. A reference angle θ3 is preset, and the angle θ1 and the angle θ2 of the microcrack reference line are compared. If θ1<θ2, then θ3=θ1; if θ2<θ1, then θ3=θ2; if θ1=θ2, then θ3=θ1=θ2; The processing unit counts the number of pixels arranged in the vertical direction Wpix between each microcrack and its own reference line in the image information, calculates the reference line pixel length Lpix of each microcrack in the image information, and calculates the maximum depth D of each microcrack in the depth information; The processing unit presets weight coefficients w1, w2 and w3, and the weight coefficients w1, w2 and w3 satisfy the condition w1+w2+w3=1. The specific values ​​of the weight coefficients w1, w2 and w3 are determined according to the number of microcracks in the tunnel, and the adjustment parameter fix is ​​preset. The initial values ​​of the adjustment parameter fix are 0.8, 0.5 and 0.3, respectively, corresponding to slight, ordinary and severe microcracks; The evaluation result is slight micro cracks, and the analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is a common microcrack. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcracks. The evaluation result is serious microcracks. The analysis unit is based on the formula Calculate the spray point Pst and spray volume Q of the microcrack, where Pst(θ) is the angle between the spray point Pst and the midpoint of the reference line, and Pst(L) is the distance between the spray point Pst and the midpoint of the reference line. The microcrack prediction program stops. The update process of the adjustment parameter fix is ​​as follows: The processing unit calculates the distance Dn between the newly added microcrack coordinates and the spray point Pst. If the value of the distance Dn is equal to or greater than the length of the microcrack reference line, the initial value of the adjustment parameter fix is ​​adjusted down by one value. Conversely, if the value of the distance Dn is less than the length of the microcrack reference line, the initial value of the adjustment parameter fix is ​​adjusted up by one value.

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